In this paper, we propose a novel formulation of the network clique detection problem by introducing a general network data representation framework. We show connections between o...
Xiaoye Jiang, Yuan Yao, Han Liu, Leonidas J. Guiba...
—Wireless neural recording systems are subject to stringent power consumption constraints to support long-term recordings and to allow for implantation inside the brain. In this ...
Zainul Charbiwala, Vaibhav Karkare, Sarah Gibson, ...
A nonparametric version of the basis pursuit method is developed for field estimation. The underlying model entails known bases, weighted by generic functions to be estimated fro...
Consider the decomposition of a signal into features that undergo transformations drawn from a continuous family. Current methods discretely sample the transformations and apply s...
Chaitanya Ekanadham, Daniel Tranchina, Eero P. Sim...
This paper analyzes and improves the linearized Bregman method for solving the basis pursuit and related sparse optimization problems. The analysis shows that the linearized Bregma...
We consider the problem of recovering a matrix from its action on a known vector in the setting where the matrix can be represented efficiently in a known matrix dictionary. Conne...
The basis pursuit problem seeks a minimum one-norm solution of an underdetermined least-squares problem. Basis pursuit denoise (BPDN) fits the least-squares problem only approximat...
We consider signals and operators in finite dimension which have sparse time-frequency representations. As main result we show that an S-sparse Gabor representation in Cn with re...
We investigate the problem of reconstructing sparse multivariate trigonometric polynomials from few randomly taken samples by Basis Pursuit and greedy algorithms such as Orthogona...
Finding the sparsest solution for an under-determined linear system of equations D = s is of interest in many applications. This problem is known to be NP-hard. Recent work studie...